Similar to most learning-based MVS methods [1]}, [2]}, the depth loss \(\mathcal {L}_{depth}\)  is defined by \(L1\)  loss between the predicted depth and the ground truth depth. Because our method includes 4 stages, there are four depth loss \(\lbrace \mathcal {L}_{depth}^{(l)}\rbrace _{l=0}^3\) . Finally, the total loss \(\mathcal {L}_{total}\)  is defined as a sum of two mentioned losses \(\mathcal {L}_{total} = 5 \mathcal {L}_{feat} + \sum _{l=0}^3 \mathcal {L}_{depth}^{(l)}\)
